Electronic data processing uses integrated and distributed computer systems with complex architecture. Coupling different computers over networks (e.g., Internet) enhances functionality but adds complexity and increases maintenance.
Each computer system operates in the complexity of hardware (e.g., computers and network) and software (e.g., operating systems, applications, databases).
Problems are deviations from the predefined operation of the computer system that are caused by malfunction of hardware or software or by improper input by the user. To name a few examples, components like processors suddenly fail, applications occasionally provide wrong results, and users sometimes manipulate data.
Problems often remain hidden from the user. Once detected, the user engages in problem solving. For example, the user reads documentation papers, activates help functions (e.g., predefined advices, often obtained via online services), looks up in databases to identify advices (“notes”), makes experiments, or tells problem symptoms to specialists (e.g., through phone hotline, email, Internet portal).
A majority of users relies on passive assistance; only a minority actively solves the problem. There are further challenges: For example, sensitive data remains with the authorized user but is shielded from specialists (data protection); users and specialists might introduce further errors. In any case, problem solving remains time consuming and expensive.
Further, heterogeneous system landscapes have systems that differ for example, by manufacturer, release version, and application. Each difference increases the number of potential problems and corresponding solutions. Selecting solutions becomes critical.
There is a need to improve problem solving by mitigating disadvantages of the prior art.